Targeted and untargeted cross-sectional study for sex-specific identification of plasma biomarkers of COVID-19 severity

Abstract

Coronavirus disease 2019 is a highly contagious respiratory illness caused by the coronavirus SARS-CoV-2. Symptoms can range from mild to severe and typically appear 2-14 days after virus exposure. While vaccination has significantly reduced the incidence of severe complications, strategies for the identification of new biomarkers to assess disease severity remains a critical area of research. Severity biomarkers are essential for personalizing treatment strategies and improving patient outcomes. This study aimed to identify sex-specific biomarkers for COVID-19 severity in a Chilean population (n = 123 female, n = 115 male), categorized as control, mild, moderate, or severe. Data were collected using clinical biochemistry parameters and mass spectrometry-based metabolomics and lipidomics to detect alterations in plasma cytokines, metabolites, and lipid profiles related to disease severity. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed to select significant characteristic features for each group. The results revealed distinct biomarkers for males and females. In males, COVID-19 severity of was associated with inflammation parameters, triglycerides content, and phospholipids profiles. For females, liver damage parameters, triglycerides content, cholesterol derivatives, and phosphatidylcholine were identified as severity biomarkers. For both sexes, most of the biomarker combinations evaluated got areas under the ROC curve greater than 0.8 and low prediction errors. These findings suggest that sex-specific biomarkers can help differentiate the levels of COVID-19 severity, potentially aiding in the development of tailored treatment approaches.

Keywords: Clinical biochemistry; SARS-CoV-2; Severity; Sex-specific; Untargeted metabolomics.